Epi-Clock: A sensitive platform to help understand pathogenic disease outbreaks and facilitate the response to future outbreaks of concern

Abstract

Determining how viruses originated and diverged and how infectious diseases are transmitted are serious challenges. Surprisingly, some inter-species genetic distances among Coronaviridae were shorter than intra-species distances, possibly representing the intermediate states of different species or subspecies in the evolutionary history of Coronaviridae. The indels of whole genome sequences between different hosts were separately associated with new functions or turning points, clearly indicating their important roles in the host transmission and shifts of Coronaviridae. Furthermore, we believe that non-nucleosomal DNA may play dominant roles in the divergence of different lineages of SARS-CoV-2 in different regions of the world because of the lack of nucleosome protection. We suggest that strong selective variation among different lineages of SARS-CoV-2 is required to produce strong codon usage bias. Interestingly, we found that an increasing number of other types of substitutions, such as those resulting from the hitchhiking effect, have accumulated, especially in the pre-breakout phase. To predict potential epidemic outbreaks, we tested our strategy, Epi-Clock, which applies the ZHU algorithm on different SARS-CoV-2 datasets to search for real significant mutational accumulation patterns correlated with the outbreak events. We could accurately predict the potential pre-phase of outbreaks with a median interval of 5 days before the outbreaks. Using our pipeline, users may review updated information on the website https://bioinfo.liferiver.com.cn with easy registration. Therefore, we propose Epi-Clock, a sensitive platform similar to a clock that can signal the need to assist individuals at focal locations by using diagnostics, isolation control, vaccines or therapy at any time.